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- aggregation classification "A1".
- aggregation creator B814863.
- aggregation creator B814864.
- aggregation creator B814865.
- aggregation creator person.
- aggregation date "2007".
- aggregation format "application/pdf".
- aggregation hasFormat 4124138.bibtex.
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- aggregation hasFormat 4124138.doc.
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- aggregation isPartOf urn:issn:0016-6731.
- aggregation language "eng".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Biology and Life Sciences".
- aggregation title "The population biology of bacterial plasmids: a hidden Markov model approach".
- aggregation abstract "Horizontal plasmid transfer plays a key role in bacterial adaptation. In harsh environments, bacterial populations adapt by sampling genetic material from a horizontal gene pool through self-transmissible plasmids, and that allows persistence of these mobile genetic elements. In the absence of selection for plasmid-encoded traits it is not well understood if and how plasmids persist in bacterial communities. Here we present three models of the dynamics of plasmid persistence in the absence of selection. The models consider plasmid loss (segregation), plasmid cost, conjugative plasmid transfer, and observation error. Also, we present a stochastic model in which the relative fitness of the plasmid-free cells was modeled as a random variable affected by an environmental process rising a hidden Markov model (HMM). Extensive simulations showed that the estimates from the proposed model are nearly unbiased. Likelihood-ratio tests showed that the dynamics of plasmid persistence are strongly dependent on the host type. Accounting for stochasticity was necessary to explain four of seven time-series data sets, thus confirming that plasmid persistence needs to be understood as a stochastic process. This work can be viewed as a conceptual starting point under which new plasmid persistence hypotheses can be tested.".
- aggregation authorList BK1187789.
- aggregation endPage "968".
- aggregation issue "2".
- aggregation startPage "957".
- aggregation volume "176".
- aggregation aggregates 4124919.
- aggregation isDescribedBy 4124138.
- aggregation similarTo genetics.106.061937.
- aggregation similarTo LU-4124138.